R^2 vs. -log10(pvalue), stratified by country number and gender

## Warning: Removed 33 rows containing missing values (geom_point).
## Warning: Removed 24 rows containing missing values (geom_point).

Odds Ratio vs. -log10(pvalue)

I^2 vs. -log10(pvalue), stratified by survey number and gender

## Warning: Removed 3 rows containing missing values (geom_point).

Describing the distribution of the associations

Summary Tables

## `summarise()` regrouping output by 'num_country_bin' (override with `.groups` argument)
gender n q_25_or q_50_or q_75_or q_25_I2 q_50_I2 q_75_I2 q_25_r2 q_50_r2 q_75_r2
(0,1]
f 4543 1.20 1.62 3.69 0.00 0.00 0.00 8.56 × 10−5 3.58 × 10−4 1.17 × 10−3
m 4089 1.24 1.78 12.67 0.00 0.00 0.00 8.39 × 10−5 3.29 × 10−4 1.12 × 10−3
(1,10]
f 1702 1.19 1.67 136.40 0.00 62.10 99.01 2.56 × 10−4 6.30 × 10−4 1.39 × 10−3
m 1488 1.24 2.30 526.30 0.00 64.85 99.14 2.42 × 10−4 5.91 × 10−4 1.26 × 10−3
(10,20]
f 467 1.15 3.93 110.95 49.80 98.59 99.39 4.10 × 10−4 7.67 × 10−4 1.22 × 10−3
m 368 1.17 3.44 189.43 47.49 98.38 99.41 4.09 × 10−4 7.70 × 10−4 1.57 × 10−3
(20,30]
f 539 1.17 1.65 9.88 56.04 97.57 99.35 4.77 × 10−4 8.42 × 10−4 1.42 × 10−3
m 343 1.26 3.68 56.47 67.70 99.14 99.48 4.71 × 10−4 7.10 × 10−4 1.22 × 10−3
## `summarise()` regrouping output by 'num_country_bin' (override with `.groups` argument)
gender n q_25_or q_50_or q_75_or q_25_I2 q_50_I2 q_75_I2 q_25_r2 q_50_r2 q_75_r2
(0,1]
f 209 2.69 871,167.69 3,311,394.30 0.00 0.00 0.00 1.64 × 10−3 3.22 × 10−3 7.64 × 10−3
m 236 1,016,942.20 3,344,900.40 6,751,671.86 0.00 0.00 0.00 1.60 × 10−3 2.50 × 10−3 5.86 × 10−3
(1,10]
f 39 1.55 1.98 14,451.18 0.00 10.48 67.59 1.68 × 10−3 2.63 × 10−3 4.80 × 10−3
m 38 2.31 443,747.77 2,182,770.88 0.00 0.60 86.23 1.28 × 10−3 1.84 × 10−3 3.54 × 10−3
(10,20]
f 35 1.34 1.51 1.92 21.63 51.69 73.08 1.25 × 10−3 1.94 × 10−3 3.20 × 10−3
m 34 1.39 1.56 1.90 17.25 50.51 61.30 1.73 × 10−3 2.27 × 10−3 5.17 × 10−3
(20,30]
f 90 1.36 1.57 1.77 48.98 65.01 75.69 1.72 × 10−3 2.61 × 10−3 3.76 × 10−3
m 36 1.26 1.48 1.87 59.49 64.83 82.21 1.47 × 10−3 2.42 × 10−3 3.14 × 10−3
## `summarise()` ungrouping output (override with `.groups` argument)
gender n q_25_or q_50_or q_75_or q_25_I2 q_50_I2 q_75_I2 q_25_r2 q_50_r2 q_75_r2
f 31 1.42 1.57 1.82 57.99 69.43 75.01 2.03 × 10−3 2.93 × 10−3 4.02 × 10−3
m 16 1.20 1.39 1.62 59.49 60.60 75.39 1.72 × 10−3 2.51 × 10−3 6.01 × 10−3

ECDFs of effect sizes

## Warning: Removed 16 rows containing non-finite values (stat_ecdf).

Identified Associations

## `summarise()` regrouping output by 'name' (override with `.groups` argument)
sig n
f
FALSE 6878
TRUE 373
m
FALSE 5944
TRUE 344

Top Associations for females across 20-29 countries in Sub-Saharan Africa

## Warning: Removed 1 rows containing missing values (geom_point).

## Warning: Removed 1 rows containing missing values (geom_point).

## Warning: Removed 1 rows containing missing values (geom_point).

Top Associations for males across 20-29 countries in Sub-Saharan Africa

Concordance of Odds Ratios of males vs. females across Sub-Saharan Africa

Country by country correlation for males

##       25%       50%       75% 
## 0.1029621 0.2047824 0.3064261

Country by country correlation for females

##       25%       50%       75% 
## 0.1486389 0.2627353 0.3701838

Country-by-country correlation of correlations

##                     correlation_females correlation_males
## correlation_females           1.0000000         0.4923484
## correlation_males             0.4923484         1.0000000